Archives: Resources

Weaving Ecosystem Services into Impact Assessment: Technical Appendix

Resource Key: 7PK2CYDD

Document Type: Report



  • Florence Landsberg
  • Jo Treweek
  • M. Mercedes Stickler
  • Norbert Henninger
  • Orlando Venn

Creators Name: {mb_resource_zotero_creatorsname}

Place: Washington D.C.

Institution: World Resources Institute

Date: 2014


This technical appendix is designed for Environmental and Social Impact Assessment (ESIA) practitioners who require a detailed, technical understanding of the Ecosystem Services Review for Impact Assessment (ESR for IA) method. It walks practitioners through each step of the method, and describes the specific output generated through each step. Although this appendix sets out the complete ESR for IA method, it is not meant to stand alone. To understand the context in which the method evolved and the challenges it is designed to address, readers should first consult the Background and Method Overview sections of Weaving Ecosystem Services Into Impact Assessment: A Step-by-Step Method (Version 1.0) (Landsberg et al. 2013). Before delving into the method’s implementation, this technical appendix addresses two issues that ESIA practitioners will face early in the ESR for IA process. First, it distinguishes between “intermediate” and “final” ecosystem services—a distinction that is relevant for assessing both project impacts and project dependencies on ecosystem services. Second, it addresses the specificities of stakeholder engagement, answering the practical questions of which stakeholders to engage and how to engage them. These issues while important for practitioners applying the ESR for IA, are less relevant for a broader audience and therefore do not feature as prominently in Landsberg et al. 2013. Finally, the technical appendix brings the ESR for IA to life through a step-by-step application of its method to an illustrative mining project in the Arctic. The case study is designed to help ESIA practitioners think through and learn from the issues that could arise in a “real life” application of the ESR for IA method.

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